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update jmlr.org urls -> proceedings.mlr.press
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R/initializers.R

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@@ -206,7 +206,7 @@ initializer_lecun_normal <- function(seed = NULL) {
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#' @inheritParams initializer_random_normal
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#'
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#' @section References:
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#' Glorot & Bengio, AISTATS 2010 <https://jmlr.org/proceedings/papers/v9/glorot10a/glorot10a.pdf>
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#' Glorot & Bengio, AISTATS 2010 <https://proceedings.mlr.press/v9/glorot10a/glorot10a.pdf>
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#'
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#' @family initializers
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#'
@@ -228,7 +228,7 @@ initializer_glorot_normal <- function(seed = NULL) {
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#' @inheritParams initializer_random_normal
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#'
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#' @section References:
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#' Glorot & Bengio, AISTATS 2010 https://jmlr.org/proceedings/papers/v9/glorot10a/glorot10a.pdf
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#' Glorot & Bengio, AISTATS 2010 <https://proceedings.mlr.press/v9/glorot10a/glorot10a.pdf>
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#'
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#' @family initializers
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#'

R/layers-convolutional.R

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@@ -1308,7 +1308,7 @@ layer_cropping_3d <- function(object, cropping = list(c(1L, 1L), c(1L, 1L), c(1L
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#' @param unit_forget_bias Boolean. If TRUE, add 1 to the bias of the forget
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#' gate at initialization. Use in combination with `bias_initializer="zeros"`.
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#' This is recommended in [Jozefowicz et
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#' al.](https://www.jmlr.org/proceedings/papers/v37/jozefowicz15.pdf)
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#' al.](https://proceedings.mlr.press/v37/jozefowicz15.pdf)
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#' @param kernel_regularizer Regularizer function applied to the `kernel`
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#' weights matrix.
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#' @param recurrent_regularizer Regularizer function applied to the
@@ -1450,7 +1450,7 @@ layer_conv_lstm_2d <- function(object, filters, kernel_size, strides = c(1L, 1L)
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#' @param unit_forget_bias Boolean. If TRUE, add 1 to the bias of the forget gate at
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#' initialization. Use in combination with `bias_initializer="zeros"`. This
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#' is recommended in [Jozefowicz et al., 2015](
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#' https://www.jmlr.org/proceedings/papers/v37/jozefowicz15.pdf)
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#' https://proceedings.mlr.press/v37/jozefowicz15.pdf)
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#'
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#' @param kernel_regularizer Regularizer function applied to the `kernel` weights
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#' matrix.
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#' @param unit_forget_bias Boolean. If TRUE, add 1 to the bias of the forget gate at
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#' initialization. Use in combination with `bias_initializer="zeros"`. This
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#' is recommended in [Jozefowicz et al., 2015](
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#' https://www.jmlr.org/proceedings/papers/v37/jozefowicz15.pdf)
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#' https://proceedings.mlr.press/v37/jozefowicz15.pdf)
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#'
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#' @param kernel_regularizer Regularizer function applied to the `kernel` weights
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#' matrix.

R/layers-recurrent-cells.R

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@@ -378,7 +378,7 @@ function(cells, ...)
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#' @param unit_forget_bias Boolean (default `TRUE`). If TRUE, add 1 to the bias of
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#' the forget gate at initialization. Setting it to true will also force
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#' `bias_initializer="zeros"`. This is recommended in [Jozefowicz et
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#' al.](https://www.jmlr.org/proceedings/papers/v37/jozefowicz15.pdf)
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#' al.](https://proceedings.mlr.press/v37/jozefowicz15.pdf)
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#'
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#' @param kernel_regularizer Regularizer function applied to the `kernel` weights
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#' matrix. Default: `NULL`.

R/layers-recurrent.R

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@@ -234,7 +234,7 @@ layer_cudnn_gru <- function(object, units,
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#' @param unit_forget_bias Boolean. If TRUE, add 1 to the bias of the forget
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#' gate at initialization. Setting it to true will also force
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#' `bias_initializer="zeros"`. This is recommended in [Jozefowicz et
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#' al.](https://www.jmlr.org/proceedings/papers/v37/jozefowicz15.pdf)
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#' al.](https://proceedings.mlr.press/v37/jozefowicz15.pdf)
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#'
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#' @template roxlate-recurrent-layer
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#'

man/initializer_glorot_normal.Rd

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man/initializer_glorot_uniform.Rd

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man/layer_conv_lstm_1d.Rd

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man/layer_conv_lstm_2d.Rd

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man/layer_conv_lstm_3d.Rd

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man/layer_cudnn_lstm.Rd

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